Genetic Polymorphisms in SCN1A Gene (rs6432860) and Pharmacoresistance to Antiepileptic Drugs Among Jordanian Patients with Epilepsy

Background: We investigated whether common variants in SCN1A are associated with antiepileptic drug (AED) non-response in Jordanian patients with epilepsy. Methods: We recruited 114 patients (105 successfully genotyped) and Sanger-sequenced five loci spanning rs6432860 and its flanking region of rs1531380, rs1531379, rs1531378, and rs10198801. Genotype–response associations were tested using contingency analyses and multivariable logistic regression adjusting for age at the time of the interview, number of AEDs, and carbamazepine use. Pre-specified secondary analyses included (i) stratification by AED class (voltage-gated sodium channel [VGSC]-acting vs. non-VGSC agents) and (ii) sensitivity analyses using alternative non-response thresholds (seizures > 0/year and ≥4/year). Linkage disequilibrium (LD) and exact Hardy–Weinberg equilibrium (HWE) tests were evaluated. Cohort minor allele frequencies (MAFs) were compared with global population estimates. Results: The four upstream previously cataloged intronic variant SNPs (rs1531380, rs1531379, rs1531378, and rs6432860) were in a complete pattern of LD association in this population (D′ = 1; r2 = 1) whereas each upstream variant with rs10198801 showed D′ = 1 with inverse correlation (r ≈ −0.53). All loci conformed to the exact HWE tests. Upstream variants had novel associations with a non-response in unadjusted analyses and remained significant after adjustment (genotype aOR = 2.8; 95% CI = 1.1–7.2; p value = 0.03), alongside independent effects of carbamazepine use (aOR = 3.3; 95% CI = 1.3–8.0; p value = 0.009) and a number of AEDs (aOR = 0.17; 95% CI = 0.06–0.50; p value = 0.002). In AED-class stratification, upstream additional intronic variants had novel associations with a non-response among VGSC-treated patients (OR = 3.8; 95% CI = 1.1–13.6; p value = 0.03) whereas rs10198801 was associated among non-VGSC patients (OR = 7.9; 95% CI = 0.9–70; p value = 0.04). Findings were robust using a ≥4 seizures/year threshold (recessive model significant) but not using any seizures > 0/year. Cohort MAFs for upstream variants (~48.6%) exceeded European, African, and Asian estimates. Significance: SCN1A upstream intronic variation has a novel association with AED non-response in the Jordanian cohort, shows mechanism-aligned patterns by AED class, persists after covariate adjustment and under a clinically used seizure-frequency threshold, and warrants ancestry-informed replication and functional validation.

Authors

Institutions

Publication Details

Journal
Pharmaceuticals
Published
2026-04-30
DOI
https://doi.org/10.3390/ph19050712
Primary Topic
Epilepsy research and treatment
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genetic Polymorphisms in SCN1A Gene (rs6432860) and Pharmacoresistance to Antiepileptic Drugs Among Jordanian Patients with Epilepsy

Rami Abduljabbar, Shayma Abdullah, Al-Motassem Yousef, Ayat Al-Farhood et al.
Pharmaceuticals
Epilepsy research and treatment
article

Genetic Polymorphisms in SCN1A Gene (rs6432860) and Pharmacoresistance to Antiepileptic Drugs Among Jordanian Patients with Epilepsy

Rami Abduljabbar, Shayma Abdullah, Al-Motassem Yousef, Ayat Al-Farhood, Hanen Al-Sadir, Ali Abuhaliema, Violet Kasabri
article en

Abstract

Background: We investigated whether common variants in SCN1A are associated with antiepileptic drug (AED) non-response in Jordanian patients with epilepsy. Methods: We recruited 114 patients (105 successfully genotyped) and Sanger-sequenced five loci spanning rs6432860 and its flanking region of rs1531380, rs1531379, rs1531378, and rs10198801. Genotype–response associations were tested using contingency analyses and multivariable logistic regression adjusting for age at the time of the interview, number of AEDs, and carbamazepine use. Pre-specified secondary analyses included (i) stratification by AED class (voltage-gated sodium channel [VGSC]-acting vs. non-VGSC agents) and (ii) sensitivity analyses using alternative non-response thresholds (seizures > 0/year and ≥4/year). Linkage disequilibrium (LD) and exact Hardy–Weinberg equilibrium (HWE) tests were evaluated. Cohort minor allele frequencies (MAFs) were compared with global population estimates. Results: The four upstream previously cataloged intronic variant SNPs (rs1531380, rs1531379, rs1531378, and rs6432860) were in a complete pattern of LD association in this population (D′ = 1; r2 = 1) whereas each upstream variant with rs10198801 showed D′ = 1 with inverse correlation (r ≈ −0.53). All loci conformed to the exact HWE tests. Upstream variants had novel associations with a non-response in unadjusted analyses and remained significant after adjustment (genotype aOR = 2.8; 95% CI = 1.1–7.2; p value = 0.03), alongside independent effects of carbamazepine use (aOR = 3.3; 95% CI = 1.3–8.0; p value = 0.009) and a number of AEDs (aOR = 0.17; 95% CI = 0.06–0.50; p value = 0.002). In AED-class stratification, upstream additional intronic variants had novel associations with a non-response among VGSC-treated patients (OR = 3.8; 95% CI = 1.1–13.6; p value = 0.03) whereas rs10198801 was associated among non-VGSC patients (OR = 7.9; 95% CI = 0.9–70; p value = 0.04). Findings were robust using a ≥4 seizures/year threshold (recessive model significant) but not using any seizures > 0/year. Cohort MAFs for upstream variants (~48.6%) exceeded European, African, and Asian estimates. Significance: SCN1A upstream intronic variation has a novel association with AED non-response in the Jordanian cohort, shows mechanism-aligned patterns by AED class, persists after covariate adjustment and under a clinically used seizure-frequency threshold, and warrants ancestry-informed replication and functional validation.

PharmaceuticalsVol. 19(5)
Al-Ahliyya Amman University (JO), University of Jordan (JO)
University of Jordan
Good health and well-being
Openalex Percentile: Top 8%
Epilepsy research and treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.